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As a result of rural settlements moving and relocation for coal mining and rural settlements expansion for new village construction, the rural settlements have been dramatically changed in the mixed mining-rural-settlement area of the Pinglu District of Shuozhou City in northern Shanxi Province of China. There are few studies that assess the characteristics and reasons of rural settlement changes...
Mining activities has caused long-term change in land surface and hydrological cycle. Accurate information of vegetation structure is important for assessing how mining activities affect ecosystem in mining areas. A remote sensing method based on vegetation cover monitoring and assessment by using Landsat data sets with the temporal coverage from 1989 to 2015 was presented and applied to the Pingshuo...
Multi-seasonal TM, ETM+ and OLI remote sensing images data of Jaozuo city in 1988, 1993, 2001, 2004, 2010 and 2014 were classified by using Random Forests algorithm. The dynamic of land use/cover was then obtained and related to the main driving factors. The results showed that: (1) DEM was more important than other variables during the process of classification, especially for forest; (2) the area...
The planted acreage estimation for major crops by using remote sensing is typically combine the sample data from ground survey with information derived from image classification, and the common applied approaches are regression estimator by using linear model and calibration estimator by using confusion matrix. In general, the crop acreage estimation for provincial level in China only satisfied the...
The pattern set of a remote sensing image contains many kinds of uncertainties. Uncertain information can create imperfect expressions for pattern sets in various pattern recognition algorithms, such as clustering algorithms. Methods based the fuzzy c-means algorithm can manage some uncertainties. As soft clustering methods, They are known to perform better on auto classification of remote sensing...
Ship detection using high resolution remote sensing images is a hot research topic in both military and civilian applications. In this paper, a new method for detection of ships docked in a harbor was proposed, in which, Harris corner detector combined with local salient region analysis were used to extract the obvious sharp-angled feature related to the fore part of a ship in satellite images. This...
The individual tree information is the most important parameter of biomass inversion. Recently, LiDAR has been widely and successfully applied in forest research, and it shows promise to map individual trees in complex and heterogeneous forests. Based on Airborne LiDAR point cloud, this paper uses local maximum filtering technique to extract the height and crown of individual tree of Qinghai spruce...
To take advantage of conventional hard land use/cover change detection method (HLUCD) and soft land use/cover change detection method (SLUCD), we develop a soft and hard land use/cover change detection method (SHLUCD) for crop distribution mapping. Two HJ-1/CCD images, acquired on 6 October 2011 (T1) and 16 April 2012 (T2) which represented the period of sowing and jointing respectively, were utilized...
To acquire the planted acreage of major grain crops and their spatial distribution in an timely, accurate, quantitative and periodic way is of significance for making a socio-economic development plans at various levels of government, and improving the operational management for relevant enterprises and farmers. The National Bureau of statistics of China (NBS) aims to take the fully advantages of...
An Extended Support Vector Machine (ESVM), which could improve the conventional change detection methods by purifying thematic classification results and neglecting of the side effect by mixed pixel, is proposed for crop acreage measurement by multi-temporal remote sensing land cover change. The ESVM method combines the concept of hard and soft classification and divides the study objects into winter...
In this paper, multi-classifier system (MCS) is applied to the automatic classification of remote sensing images, and some effective multi-classifier fusion methods with relatively high accuracy are proposed based on substantive experiments. The classification accuracy of MCS has been remarkably improved compared to single classifier with an average increment of 5%. In addition, a diversity measure...
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